Daniel G. Aliaga
Associate Professor of Computer Science, Purdue University
Education: Daniel Aliaga holds BS in Computer Science, honors thesis (with Andy van Dam) and magna cum laude, from Brown University. Subsequently, obtained a MS (with Henry Fuchs) and a PhD degree (with Anselmo Lastra, Fred Brooks, and Dinesh Manocha) in Computer Science from UNC Chapel Hill. Worked at Nokia/Lucent/AT\&&T Bell Labs (with Ingrid Carlbom) and at Princeton University as a researcher (with Tom Funkhouser). He joined Purdue in 2003, co-founding the Computer Graphics and Visualization Laboratory (CGVLAB). Dr. Aliaga has held visiting professor positions at ETH Zurich Information Architecture and also ETH Computer Science, INRIA Sophia-Antipolis, and KAUST in Saudi Arabia. After finishing high school (Colegio Santa Maria), Daniel immigrated from Lima, Peru and is the first in his family and relatives to hold a PhD.
Products: Dr. Aliaga's first computer graphics publication was in 1991 and he now has over 140 refereed publications covering multiple disciplines, holds membership in 80+ program committees, has on-going international multi-disciplinary collaborations (i.e., with computer science, urban planning, architecture, meteorology, atmospheric/earth sciences, engineering, archaeology, and more), and has given over 50 invited talks (in the US, Brasil, Colombia, Ecuador, France, Japan, Korea, Peru, Qatar, Sweden, and Switzerland). Further, Dr. Aliaga has been technical advisor on multiple startups (Synthicity, UrbanSim, Authentise).
Service and Awards: Daniel is Associate Editor for IEEE TVCG and for Visual Computing Journal (previously for Computer Graphics Forum and Graphical Models) and PC member for SIGGRAPH, CVPR, ICCV, Eurographics, AAAI, I3D, IEEE Vis. He has received a Fulbright Scholar Award, a Discovery Park Faculty Research Fellowship, and his PhD advisees have received a total of 11 Purdue fellowships/grants. He is a member of ACM SIGGRAPH and ACM SIGGRAPH Pioneers, and has multiple times been Chair of Faculty Diversity for College of Science at Purdue.
Lawson Computer Science Building, Rm 3177
305 N. University St,
West Lafayette, IN 47907-2107
Phone: 765-494-6010 (main office)
Email: aliaga at cs dot purdue dot edu
In this multi-disciplinary project, Dr. Aliaga's group has since 2009 collaborated with numerous experts in urban planning, atmospheric/geological sciences, civil engineering, architecture, hydrology, and transportation engineering to capture, simulate, and modify models of urban environments. Today, more than half of the world's population of 7 billion people lives in cities - and that number is only expected to grow. Cities, and urban spaces of all sizes, are however extremely complex and their modeling is still not solved. Dr. Aliaga pursues urban visual computing and artificial intelligence (AI) tools for improving the complex urban ecosystem and for "what-if" exploration of sustainable urban designs, including integrating urban 3D modeling, simulation, meteorology, vegetation, and traffic modeling. To date, he has developed several algorithms, deployed cyberinfrastructure prototypes using ground-level imagery, aerial imagery, satellite imagery, GIS data, and forward and inverse procedural modeling to create/modify 3D and 2D urban models, given numerous international talks, TEDx talk, and driven-forward global efforts (e.g., WUDAPT).
Modeling Large-Scale Heatwave by Incorporating Enhanced Urban Representation.
P. Patel, S. Jamshidi, R. Nadimpalli, D. Aliaga, G. Mills, F. Chen, M. Demuzere, D. Niyogi. Journal of Geophysical Research: Atmospheres, 2022
Automatic Deep Inference of Procedural Cities from Global-Scale Spatial Data.
X. Zhang, A. Shehata, B. Benes, D. Aliaga. ACM Transactions on Spatial Algorithms and Systems, 2021
Impact of green roofs on heavy rainfall in tropical, coastal urban area.
P. Patel, S. Karmakar, S. Ghosh, D. Aliaga, D. Niyogi. Environmental Research Letters (ERL), 2021.
Design and Deployment of Photo2Building: A Cloud-based Procedural Modeling Tool as a Service.
M. Bhatt, R. Kalyanam, G. Nishida, L. He, C. May, D. Niyogi, D. Aliaga, Practice and Experience in Advanced Research Computing (PEARC), 2020
Pathway using WUDAPT's Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling.
J. Ching, D. Aliaga, G. Mills, V. Masson, L. See, M. Neophytou, A. Middel, A. Baklanov, C. Ren, E. Ng, J. Fung, M. Wong, Y. Huang, A. Martilli, O. Brousse, I. Stewart, X. Zhang, A. Shehata, D. Niyogi, Urban Climate, 2019
Urban Walkability Design using Virtual Population Simulation.
T. Mathew, P. Knob, S. Musse, D. Aliaga, Computer Graphics Forum (CGF), 2019
Procedural Generation of Flood-Sensitive Urban Layouts.
A. Mustafa, X. Zhang, G. Nishida, M. Bruwier, B. Dewals, J. Teller, D. Aliaga, Environment and Planning B: Urban Analytics and City Science, 2018
Fast Weather Simulation for Inverse Procedural Design of 3D Urban Models.
I. Garcia-Dorado, D. Aliaga, P. Bhalachandran, P. Schmid, D. Niyogi, ACM Transactions on Graphics (TOG), 2017
Designing Large-Scale Interactive Traffic Animations for Urban Modeling.
I. Garcia-Dorado, D. Aliaga, S. Ukkusuri, Computer Graphics Forum (CGF), 2014
Visualization-based Decision Tool for Urban Meteorological Modeling.
D. Aliaga, C. Vanegas, M. Lei, D. Niyogi. Environment and Planning B: Planning and Design, 2013
Interactive Design of Urban Spaces using Geometrical and Behavioral Modeling.
C. Vanegas, D. Aliaga, B. Benes, P. Waddell. ACM Transactions on Graphics (TOG), 2009
Dr. Aliaga is a pioneer in the area of inverse procedural modeling for urban spaces, with his first paper introducing the topic in 2005/2007. His vision is to facilitate semi-automatic and controllable content creation and edition of large and complex geometric models for use in digital simulation, visualization, entertainment, education, and cultural heritage by converting unstructured data into organized and easily editable procedural representations. While a significant benefit of procedural modeling is its detail amplification, it is very difficult to develop a compact expressive set of procedural rules. To this end, his group has innovated many automatic methods to infer procedural model rules and parameter values from 3D models, sketches, images, point clouds, roads, facades, buildings, cities, and vegetation. More recently, this approach now includes the use of various forms of deep generative modeling and is still an active area of research. Dr. Aliaga has published surveys, given talks and tutorials (e.g., at SIGGRAPH, CVPR and Eurographics) on this topic.
Procedural Roof Generation From a Single Satellite Image.
X. Zhang, D. Aliaga. Computer Graphics Forum, 2022
Synthesis and Completion of Facades from Satellite Imagery.
X. Zhang, C. May, D. Aliaga. European Conference on Computer Vision (ECCV), 2020
Procedural Modeling of a Building from a Single Image.
G. Nishida, A. Bousseau, D. Aliaga, Computer Graphics Forum (CGF), 2018
Interactive Sketching of Urban Procedural Models,
G. Nishida, I. Garcia-Dorado, D. Aliaga, B. Benes, A. Bousseau. ACM Transactions on Graphics (TOG), 2016
Coupled Segmentation and Similarity Detection for Architectural Models.
I. Demir, D. Aliaga, B. Benes. ACM Transactions on Graphics (TOG), 2015
Procedural Editing of Building Point Clouds.
I. Demir, D. Aliaga, B. Benes, IEEE Int'l Conference on Computer Vision (ICCV), 2015
Inverse Design of Urban Procedural Models.
C. Vanegas, I. Garcia-Dorado, D. Aliaga, B. Benes, P. Waddell. ACM Transactions on Graphics (TOG), 2012
Building Reconstruction using Manhattan-World Grammars.
C. Vanegas, D. Aliaga, B. Benes. IEEE Computer Vision and Pattern Recognition (CVPR), 2010
Dr. Aliaga has developed multiple novel image processing and image-based 3D reconstruction methods. In particular, Dr. Aliaga created the photogeometric structured light method to perform high-accuracy self-calibrating 3D reconstruction. This work led to 3D spatial augmented reality techniques used to perform visual virtual restoration, showcased in several museum applications. In addition, Dr. Aliaga created a novel method to embed a genuinity signature into the surface of 3D objects to detect counterfeiting and tampering. Further, Dr. Aliaga developed custom displays and image rendering methods to compensate for human visual aberrations.
A Total Variation Approach for Customizing Imagery to Improve Visual Acuity.
C. Montalto, I. Garcia-Dorado, D. Aliaga, M. Oliveira, F. Meng. ACM Transactions on Graphics (TOG), 2015
Fast High-Resolution Appearance Editing Using Superimposed Projections.
D. Aliaga, Y. H. Yeung, A. Law, B. Sajadi, A. Majumder. ACM Transactions on Graphics (TOG), 2012
Tailored Displays to Compensate for Visual Aberrations.
V. Pamplona, M. Oliveira, D. Aliaga, R. Raskar. ACM Transactions on Graphics (TOG), 2012
Pose-Free Structure from Motion Using Depth From Motion Constraints.
J. Zhang, M. Boutin, D. Aliaga, IEEE Transactions on Image Processing (TIP), 2011
A Self-Calibrating Method for Photogeometric Acquisition of 3D Objects.
D. Aliaga, Y. Xu. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2010
A Framework for Pose-Free Modeling of 3D Scenes.
D. Aliaga, J. Zhang, M. Boutin. ACM Transactions on Graphics (TOG), 2009.
Genuinity Signatures: Designing Signatures for Verifying 3D Object Genuinity.
D. Aliaga, M. Atallah. Computer Graphics Forum (CGF), 2009
Virtual Restoration Stage for Real-World Objects.
D. Aliaga, A. Law, Y. Yeung. ACM Transactions on Graphics (TOG), 2008
High-Resolution Modeling of Moving and Deforming Objects Using Sparse Geometric and Dense Photometric Measurements.
Y. Xu, D. Aliaga, IEEE Computer Vision and Pattern Recognition (CVPR), 2010
Photogeometric Structured Light: A Self-Calibrating and Multi-Viewpoint Framework for Accurate 3D Modeling.
D. Aliaga, Y. Xu. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008
All Journals & Conferences: CGVLAB Website
(Purdue PI) Urban Simulation and Visualization
(PI) Genuinity Signatures
(PI) 3D Scene Digitization (REU)
Ph.D. Students (advisees)